Optimal control for plant production in greenhouses

Abstract In the past, greenhouse climate control has been improved by using feedback-feedforward control in combination with adaptive control algorithms and on-line adaption of model parameter. Controlled environment in greenhouses leads to a high level of intensity in plant production. Microcomputers give the possibilities to save labor. but also to raise the plant productivity to maximum by applying optimal environmental control for the individual cultivation. Optimal environmental control includes regulation of temperature and humidity, control of CO 2 -concentration, pH- and EC-values to an optimal level, and supply of artificial lighting. This results in reduced personal expenses and decreased growing periods for maximum crop harvest, combined with less overall heat consumption. Plant growth models and economic models are indispersible for optimal control of plant production. The growth models describe the plant's reaction on changing environmental factors. In order to increase the accuracy of optimization, a feedback from the plants is needed to realize an on-line adaption of model parameter. Several methods have been developed and tested to measure “plant growth”. Besides the growth models, heuristic knowledge is important to improve on-line optimization. Artificial intelligence and neurocomputing technique will be useful for this purpose.

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